Revision of Ischnopelta Stål, 1868 with the description of twenty new species (Hemiptera: Pentatomidae: Discocephalinae)

Ischnopelta Stål, 1868 is a Discocephalini genus with three known species, I. scutellata (Signoret, 1851), I. oblonga (Fieber, 1851), and I. luteicornis (Walker, 1867), and distribution restricted to South America. The examination of 284 specimens from several localities in Venezuela, Brazil, Bolivia, Argentina, and Paraguay, revealed the existence of new species. Measurements of 24 morphometric parameters were taken using stereomicroscope and tpsDig2 version 2.16 from images captured with an MShot MD50 camera coupled to a Techno RZ stereomicroscope and edited in MShot DIS version 1.1. The genitalia of both sexes was dissected upon specimen availability, digested in KOH 10%, dehydrated in ethanol 70%, stained in Congo red (when needed), and preserved in liquid glycerin. Photographs were made in a Nikon AZ100M stereomicroscope, and a focus stacking procedure was done with Nikon NIS-Elements Ar Microscope Imaging Software. Drawings were produced over the images with a vectorial image processor. In this work Ischnopelta is revised, I. scutellata and I. luteicornis are redescribed, and keys to males and females of the species are proposed. We describe 20 new species: I. alalonga sp. n., I. anangulata sp. n., I. bechyneorum sp. n., I. confusa sp. n., I. coralinae sp. n., I. cordiformis sp. n., I. crassula sp. n., I. cristulata sp. n., I. cylindrata sp. n., I. guarani sp. n., I. impunctata sp. n., I. magna sp. n., I. marginella sp. n., I. montana sp. n., I. paiagua sp. n., I. parvula sp. n., I. pellucidula sp. n., I. ruckesi sp. n., I. vellozia sp. n., and I. wigodzinskyi sp. n.. We were unable to locate the syntypes of I. oblonga (Fieber, 1851) and the species is treated here as incertae sedis.

A signed pulse-train-based image processor-array for parallel kernel convolution in vision sensors

Purpose The purpose of this paper is to design a kernel convolution processor. High-speed image processing is a challenging task for real-time applications such as product quality control of manufacturing lines. Smart image sensors use an array of in-pixel processors to facilitate high-speed real-time image processing. These sensors are usually used to perform the initial low-level bulk image filtering and enhancement. Design/methodology/approach In this paper, using pulse-width modulated signals and regular nearest neighbor interconnections, a convolution image processor is presented. The presented processor is not only capable of processing arbitrary size kernels but also the kernel coefficients can be any arbitrary positive or negative floating number. Findings The performance of the proposed architecture is evaluated on a Xilinx Virtex-7 field programmable gate array platform. The peak signal-to-noise ratio metric is used to measure the computation error for different images, filters and illuminations. Finally, the power consumption of the circuit in different operating conditions is presented. Originality/value The presented processor array can be used for high-speed kernel convolution image processing tasks including arbitrary size edge detection and sharpening functions, which require negative and fractional kernel values.